Lead Data Scientist

: 8+ Years\nJob Opportunity : Full Time (Permanent)\nLocation – Remote\n\nInterview Process –\nInternal Technical Round - 1\nClient Round – Virtual – 2\n\nJob Description: Lead Data Scientist – Generative AI & Agentic Systems\nRole Overview\nWe are seeking a highly skilled Lead Data Scientist with deep expertise (8+ years) in Generative AI, Agentic Systems, and advanced analytics to drive the design and deployment of enterprise-grade AI solutions. This role combines hands-on engineering, architectural leadership, and product thinking to build scalable AI systems aligned with business outcomes.\n\nKey Responsibilities\nLead the design and implementation of Generative AI and multi-agent systems, traditional ML for enterprise use cases\nArchitect and deploy Agentic RAG pipelines , tool-calling frameworks, MCP-based AI systems, regression/classification algorithm based solutions\nDrive end-to-end AI lifecycle : data ingestion, preprocessing, modeling, evaluation, and deployment\nCollaborate with cross-functional teams to translate business requirements into AI solutions\nEnsure production readiness , scalability, and performance optimization of AI systems\n\nRequired Skills & Competencies\nGenerative AI & Agentic AI\nMulti-Agent Systems and orchestration frameworks\nAgentic RAG architectures, tool-calling, and MCP-based systems\nLLM orchestration across OpenAI, Claude, Gemini, LLaMA\nInter-agent communication protocols (A2A, MCP)\nTraditional Machine Learning & Advanced Analytics\nStrong expertise in supervised and unsupervised learning\n(Regression, Classification, Clustering, Dimensionality Reduction)\nExperience with tree-based models (XGBoost, Random Forest, LightGBM)\nHands-on with feature engineering, feature selection, and data preprocessing\nExposure to deep learning frameworks (CNNs, RNNs, Transformers where applicable)\nAI Engineering & Data Science\nStrong foundation in Machine Learning and Deep Learning\nModel fine-tuning, evaluation, and performance optimization\nStatistical analysis, feature engineering, and data modeling\nPlatforms & Tools\nCloud: GCP/AWS/AZURE\nFrameworks: LangChain, LlamaIndex, LangGraph, CrewAI, PandasAI\nBackend & Apps: FastAPI, Streamlit, Docker\nDatabases: Pinecone, ChromaDB, Neo4j, PostgreSQL\nDeveloper Tools: GitHub, Copilot\nSoft Skills\nStrong problem-solving and analytical thinking\nExcellent communication skills —ability to explain complex AI concepts to business stakeholders\nProduct mindset with focus on business impact and usability\nAbility to lead cross-functional teams and drive alignment\nHigh level of ownership and accountability\nAdaptability in a fast-evolving AI landscape\nStrong collaboration and stakeholder management skills\nMentorship and team development capabilities\nEducation & Certifications\nBachelor’s or master’s in computer science , Electronics, Data Science, or related field\nRelevant certifications in Cloud (GCP/Azure) and Generative AI are a plus